Tag: RAG retrieval-augmented generation
Enhancing GenAI for Privacy and Performance: The Future of Personalized AI with Edge Vector Databases
The evolution of Generative AI (GenAI) is marked by a significant transition from model development to application development. As these AI models mature, the focus shifts to integrating them into real-world applications, bringing about new challenges. Application developers and infrastructure...
Genie Yuan, VP Couchbase APAC
June 26, 2024
Develop Performant RAG Apps With Couchbase and Vectorize
For technology leaders and developers, the process of integrating rich, proprietary data into generative AI applications is often filled with challenges. Vector similarity search and retrieval augmented generation are powerful tools to help with this, but one mistake extracting, chunking,...
What are Foundation Models? (Plus Types and Use Cases)
What is a Foundation Model? A foundation model is a powerful type of artificial intelligence (AI) trained on massive amounts of general data, allowing it to tackle a broad range of tasks. Foundation models, such as OpenAI’s GPT (Generative Pre-trained...
Vector Search at the Edge with Couchbase Mobile
We’re pleased to announce the public beta release of Couchbase Lite 3.2 with support for vector search. This launch follows the coattails of vector search support on Capella and Couchbase Server 7.6. Now, with the beta launch of vector search...
Priya Rajagopal, Senior Director, Product Management
March 27, 2024
An Overview of Retrieval-Augmented Generation (RAG)
What Is Retrieval-Augmented Generation? There’s no doubt that large language models (LLMs) have transformed natural language processing, but at times, they can be inconsistent, random, or even plain wrong in the responses they deliver to a prompt. While this can...
Caroline Kerns
February 21, 2024